Caffeine consumption as a predictor of sleep quality, sleep hygiene, subjective sleepiness, and academic performance among North Texas female college students
Research during the last decade of the 20th Century reveals that Americans of all age groups are rapidly becoming members of a "sleep deprived nation". In fact, sleep disturbances are More prevalent in college students than in the general population. There is a considerable need for sleep hygiene awareness among college students. Understanding the role that sleep quality plays in academic success is paramount. Data from this research adds critical information to the health educator's knowledge base by outlining the effect of caffeine on sleep hygiene. It allows educators to focus on a single component of sleep hygiene that will make the most difference in student's sleep quality.
The present study used six survey instruments to describe whether caffeine consumption was a predictive factor of sleep quality, sleep hygiene, and academic performance among female college students in North Texas. One hundred and eighty-five female participants were surveyed using an electronic version of the Sleep Hygiene Index (SHI), the Epworth Sleepiness Scale (ESS), the Caffeine Consumption Questionnaire (CCQ), the Pittsburgh Sleep Quality Index (PSQI), and the Insomniacs' Perceived Control over Sleep Questionnaire were deployed along with a general demographic questionnaire to collect data.
Descriptive statistics were used to illustrate the characteristics of the sample population as well as the dependent measures. Inferential statistics were used to test the hypotheses under study. Pearson's Product Moment Correlations were computed to test for significant relationships between the dependent variables, and between the dependent variables of the Perceived Control subscales, Sleep Hygiene, Sleepiness, GPA, and the PSQI. One way ANOVA and two-way MANOVA were conducted to test for significant differences between the dependent variables. Finally, multiple regression models were used in order to determine whether any of the demographic variables predicted the continuous dependent variables.
Caffeine intake is a positive predictor of sleep disturbances, sleepiness, and poor sleep quality. Additionally, multiple regression analysis showed that Medium-high intake of caffeine (306-487 mgs/day) predicted worse overall sleep quality as measured by the PSQI. While caffeine consumption was not found to be a significant predictor of academic performance multiple regression analysis results indicated that caffeine consumption is a significant predictor of subjective sleepiness, and a lack of perceived control of sleep.
The role of health educators and health services in meeting students' need for sleep related interventions is immense. Improving students' access to information through well-coordinated multi-media programs can have a significant impact. In fact, efforts directed at curtailing caffeine use may improve their sleep quality resulting in an increase in learning capacity and academic performance. This is especially important for women who throughout their lifespan are at a disadvantage due to their gender.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer Translations powered by LEC. Translations powered by LEC.